题目：Regression Analysis of Clustered Semi-competing Risks Data

报告人：Associate Professor Xiang Liming

School of Physical & Mathematical Sciences,

Nanyang Technological University

Abstract :

Analysis of semi-competing risks data is becoming increasingly important in medical research in which a subject may experience both nonterminal and terminal events, and the time to the intermediate nonterminal event (e.g. onset of a disease) is subject to dependent censoring by the terminal event (e.g. death) but not vice versa. Typically, both two types of events are dependent. In many applications, subjects may be nested within clusters, such as patients in a multi-center study, leading to possible association among event times due to unobserved shared factors across subjects. To incorporate dependency within clusters and association between two types of event times, we propose a new flexible semiparametric modeling framework, where the nonterminal and terminal events are jointly modeled using a copula approach and each of their marginal distributions is formulated by a Cox proportional hazards model with random effects. A nonparametric maximum likelihood estimation procedure is developed and implemented through a Monte Carlo EM algorithm. The proposed estimator is shown to enjoy desirable asymptotic properties. Results from extensive simulation studies indicate that the proposed method performs well in finite samples and is especially robust against misspecification of the random effects distribution. We further illustrate the practical utility of the method by analyzing data from a multi-institutional study of breast cancer.

时间： 11月9日（周五）上午10：00-11:30

地点：565net必赢客户端本部教二楼 727 教室